In the United States, nearly 100,000 patients receive general anesthesia and sedation daily to safely undergo surgical and non-surgical procedures. A high proportion of the patients receiving anesthesia care are elderly, and in addition may have pre-existing conditions such as Alzheimer's disease or cerebrovascular disease. As such, elderly patients have a higher risk of post-operative delirium and cognitive dysfunction. Anesthesiologists know that management of older patients requires different approaches compared with that of younger patients. For example, the dose required to achieve the same anesthetic state in elderly patients can be 50% lower than that for younger patients. Unfortunately, at present we know little about the fundamental neurophysiology of how anesthetic drugs influence the aging brain. This represents a major knowledge gap that prevents us from developing novel approaches to more safely administer anesthesia and sedation in elderly patients. In recent years, aided largely by non-invasive imaging methods, significant progress has been made in understanding systems-level neurophysiology of anesthetic effects in humans. In parallel, imaging biomarkers have advanced to enable the identification of two of the most common ?silent? pathologies that may put older adults at higher risk for poor post-anesthesia/surgical outcomes: Alzheimer's disease (AD) and cerebrovascular disease (CVD). We propose here to bring these two lines of research together with a study employing imaging markers of preclinical AD (amyloid PET, cortical atrophy) and CVD (FLAIR MRI, DTI) alongside sophisticated computational analysis of intra-operative EEG, with the goal of using these measures to better understand variability in response to anesthesia and post-operative outcomes. As we accomplish the aims of this grant, the data generated should lead to fundamental new insights into the neurophysiology of anesthesia in aging patients. These insights will advance knowledge about how to assess patients for risks of anesthesia and reduce those risks through improved brain monitoring, improved drug dosing, and a precision- medicine approach to tailoring anesthesia to the individual's brain.